Description:

This paper describes the formulation and evaluation of RLINE, a Research LINE source model for near surface releases. The model is designed to simulate mobile source pollutant dispersion to support the assessment of human exposures in near-roadway environments where a significant portion of the population spends time. The model uses an efficient numerical integration scheme to integrate the contributions of point sources used to represent a line-source. Emphasis has been placed on estimates of concentrations very near to the source line. The near-surface dispersion algorithms are based on new
formulations of horizontal and vertical dispersion within the atmospheric surface layer, details of which are described in a companion paper (Venkatram et al., 2013). This paper describes the general formulations of the RLINE model, the meteorological inputs for the model, the numerical integration techniques, the handling of receptors close to the line source, and the performance of the model against developmental data bases and near-road concentrations from independent field studies conducted along actual highway segments.

Purpose/Objective:

The National Exposure Research Laboratory′s (NERL′s)Atmospheric Modeling Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.